app.py

import os
import streamlit as st
from groq import Groq

# Set the Groq API key
os.environ["GROQ_API_KEY"] = "key"

# Initialize Groq client
client = Groq(api_key=os.environ.get("key"))

# Carbon footprint reduction data (kg CO2 per kg recycled)
carbon_reduction_data = {
    "Plastic Bottles": 3.8,
    "Glass Bottles": 0.5,
    "Metal Cans": 9.0,
    "Old Clothes": 2.0,
    "Paper and Cardboard": 1.3,
    "E-Waste": 15.0,
    "Tires": 8.0,
}

# Custom CSS for colors and layout
st.markdown(
    """
    <style>
    body {
        background-color: #f5f5f5;
    }
    .main {
        background-color: #ffffff;
        border-radius: 10px;
        padding: 20px;
        color: #333333;
    }
    .sidebar .sidebar-content {
        background-color: #dceefb;
        border-radius: 10px;
    }
    </style>
    """,
    unsafe_allow_html=True,
)

# Sidebar for navigation
st.sidebar.title("🌍 RecycleSmart-PK")
st.sidebar.image(
    "https://via.placeholder.com/300x200?text=RecycleSmart+Logo",
    use_container_width=True,
)
st.sidebar.markdown("### Navigation")
section = st.sidebar.radio(
    "Choose a section:", ["Home", "Recycle Suggestions"]
)

# Main Content
if section == "Home":
    st.title("♻️ Welcome to RecycleSmart-PK!")
    st.image(
        "https://via.placeholder.com/800x400?text=Recycle+Smartly%2C+Save+Our+Planet",
        use_container_width=True,
    )
    st.markdown(
        """
        RecycleSmart-PK helps you turn waste into opportunities while reducing your carbon footprint.  
        Navigate to **Recycle Suggestions** to start recycling smartly!
        """
    )

elif section == "Recycle Suggestions":
    st.title("💡 Recycling Suggestions")
    selected_items = st.multiselect(
        "Select items to recycle:", list(carbon_reduction_data.keys())
    )
    quantities = {
        item: st.number_input(
            f"Enter quantity for {item} (in kg):", min_value=0, step=1
        )
        for item in selected_items
    }

    if st.button("Get Suggestions"):
        if selected_items:
            total_carbon_reduction = 0
            st.write("### ♻️ Suggestions and Impact:")
            for item, quantity in quantities.items():
                if quantity > 0:
                    prompt = (
                        f"Suggest profitable and eco-friendly uses for {quantity} kg of {item}, "
                        f"including household uses and ways to monetize them."
                    )
                    chat_completion = client.chat.completions.create(
                        messages=[{"role": "user", "content": prompt}],
                        model="llama-3.3-70b-versatile",
                        stream=False,
                    )
                    llm_response = chat_completion.choices[0].message.content
                    carbon_reduction = carbon_reduction_data.get(item, 0) * quantity
                    total_carbon_reduction += carbon_reduction
                    st.write(f"**{item} ({quantity} kg)**")
                    st.write(f"💡 {llm_response}")
                    st.write(
                        f"🌍 **Carbon Footprint Reduction**: {carbon_reduction:.2f} kg CO₂"
                    )
                    st.markdown("---")
            st.write("### 🌟 Total Carbon Footprint Reduction 🌟")
            st.write(f"🌍 **{total_carbon_reduction:.2f} kg CO₂ saved**")
            st.success("🎉 Great job contributing to a greener planet!")
        else:
            st.error("❗ Please select at least one item and specify its quantity.")






"""
import os
import streamlit as st
from groq import Groq

# Set the Groq API key
os.environ["GROQ_API_KEY"] = "key"

# Initialize Groq client
client = Groq(api_key=os.environ.get("key"))

# Carbon footprint reduction data (kg CO2 per kg recycled)
carbon_reduction_data = {
    "Plastic Bottles": 3.8,
    "Glass Bottles": 0.5,
    "Metal Cans": 9.0,
    "Old Clothes": 2.0,
    "Paper and Cardboard": 1.3,
    "E-Waste": 15.0,
    "Tires": 8.0,
}

# Function to call Groq LLM
def get_recycling_suggestions_from_groq(item, quantity):
    prompt = (
        f"You are an expert in recycling and sustainability. "
        f"Suggest profitable and eco-friendly uses for {quantity} kg of {item}, "
        f"including household uses, ways to monetize them, and calculate carbon footprint reduction."
    )
    chat_completion = client.chat.completions.create(
        messages=[{"role": "user", "content": prompt}],
        model="llama-3.3-70b-versatile",
        stream=False,
    )
    return chat_completion.choices[0].message.content

# App title
st.title("♻️ Recycle with Groq LLM 🌍")
st.write("Select clutter items, specify quantities, and get tailored, profitable recycling suggestions along with carbon footprint reduction scores!")

# Multi-select input for clutter items
selected_items = st.multiselect(
    "Select items to recycle:",
    list(carbon_reduction_data.keys())
)

# Quantity input for selected items
quantities = {}
for item in selected_items:
    quantities[item] = st.number_input(
        f"Enter quantity for {item} (in kg):", min_value=0, step=1
    )

# Process and display results
if st.button("Get Recycling Suggestions"):
    if selected_items:
        total_carbon_reduction = 0
        st.write("### ♻️ Recycling Suggestions and Impact:")
        for item, quantity in quantities.items():
            if quantity > 0:
                # Call Groq LLM for dynamic suggestions
                llm_response = get_recycling_suggestions_from_groq(item, quantity)

                # Fetch carbon footprint reduction
                carbon_reduction = carbon_reduction_data.get(item, 0) * quantity
                total_carbon_reduction += carbon_reduction

                # Display results for each item
                st.write(f"**{item} ({quantity} kg)**")
                st.write(llm_response)
                st.write(f"🌍 **Carbon Footprint Reduction**: {carbon_reduction:.2f} kg CO₂")
                st.write("---")

        # Display total carbon footprint reduction credit score
        st.write("### 🌟 Your Total Carbon Footprint Reduction 🌟")
        st.write(f"🌍 **{total_carbon_reduction:.2f} kg CO₂ saved**")
        st.success("Great job contributing to a greener planet! 🌱💚")
    else:
        st.error("Please select at least one item and specify its quantity.")

# Follow-up Q&A with Groq LLM
st.write("### 🤔 Have more questions about recycling?")
user_query = st.text_input("Ask the Groq LLM about recycling:")
if st.button("Ask Groq"):
    if user_query:
        follow_up_response = client.chat.completions.create(
            messages=[{"role": "user", "content": user_query}],
            model="llama-3.3-70b-versatile",
            stream=False,
        ).choices[0].message.content
        st.write("### 🧠 Groq LLM's Answer:")
        st.write(follow_up_response)
    else:
        st.error("Please enter a question.")
        """